The Challenges of Fourth Generation Espionage

By Val LeTellier

Val LeTellier is a veteran intelligence officer. Before his career as a CIA case officer, he served as a State Department Diplomatic Security Special Agent. He has since worked with CACI, Booz Allen and Raytheon in creating specialized communication, virtual operations, and digital surveillance risk mitigation programs. He recently co-founded 4th Gen Solutions to develop next generation tradecraft capabilities for IC front-line operators.

Val LeTellier is a veteran intelligence officer.  Before his career as a CIA case officer, he served as a State Department Diplomatic Security Special Agent. He has since worked with CACI, Booz Allen and Raytheon in creating specialized communication, virtual operations, and digital surveillance risk mitigation programs.  He recently co-founded 4th Gen Solutions to develop next generation tradecraft capabilities for IC front-line operators.

OPINION — In a rare December 2018 public address, then-British Secret Intelligence Service (SIS) Chief Alex Younger, (who is now a Cipher Brief Expert) used the term ‘fourth-generation espionage’ to describe the new mindset that intelligence leaders need in order to address the challenges of the fourth industrial revolution.  He noted that “The digital era has profoundly changed our operating environment.  Bulk data combined with modern analytics make the modern world transparent.  We need to ensure that technology is on our side, not that of our opponents”.

Younger’s concerns are well founded.  The Fourth Industrial Revolution includes many new technologies that complicate clandestine activity, including “mobile devices, Internet of things (IoT) platforms, location detection technologies (electronic identification), advanced human-machine interfaces, authentication and fraud detection, smart sensors, big analytics and advanced processes, multilevel customer interaction and customer profiling, augmented reality/wearables, on-demand availability of computer system resources, and data visualization.”

In fact, the combination of ubiquitous digital surveillance and powerful data analytics is changing espionage in ways that we are only starting to understand.  Widespread automated recognition and monitoring of individuals is now possible, ‘blind spots’ are quickly being eliminated, events can be forensically examined to a degree never known, and an individual’s future actions quickly and accurately predicted.

This comes through expansive closed-circuit television (CCTV) camera placement, ‘smart city’ technologies, ad-tech data, vehicular telemetry, IoT, and 5G networks enabling omnipresent personal data collection and the data analytics to make sense of it all; machine learning that enables massive data aggregation, facial recognition for real-time monitoring and post-event investigation and pattern analysis for identifying anomalies and predicating behavior.

Finally, the artificial intelligence (AI) capabilities, ‘multi-intelligence fusion’ methodologies and correlation engines currently under development will certainly enable counterintelligence by further empowering aggregation and seamlessly integrating different sensor types.

Law enforcement and counterintelligence elements now have an exponentially growing array of digital sensors and robust analytics to collect and turn massive data pools into usable information, allowing them to increase accountability within their governments, prevent external and internal actors’ activity, and quickly investigate suspect activity.


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This ‘perfect storm’ of exploding data collection, powerful data analytics and even virus tracking creates what some have called ‘an existential threat’ to the ability of intelligence agencies to conduct mission.  To better understand these challenges and what intelligence agencies need to do to address them, it is helpful to examine the impact of the new operating environment on select human intelligence activities:

First, think about widespread personal data collection and the impossibility of privacy and effective cover.   Advanced data analytics, machine learning (ML) and AI enable the aggregation of massive data sets, the correlation of activity and the real time and forensic exposure of operations.  High-speed/high-density 5G cell networks, IoT devices and vehicle telemetry provide refined triangulation and location of an individual’s movement, further complicated by emerging issues like DNA mapping and virus tracking.

Second, think about the massive expansion of the virtual domain where many people now spend more time engaging than they do in the physical world.  The ability to operate safely, securely, sustainably, and successfully online are ‘table stakes’ for any modern-day service, underpinning a wide spectrum of activity like information collection, targeting, influencing, and recruiting.

COVID restrictions have only accelerated and reinforced this point.  Meanwhile, cyberspace is becoming more active, unforgiving, and hostile.  Data providers and social media platforms are monetizing their access through stronger authentication and adversary services are increasingly aware of traditional methodologies.  Emerging national Internet networks in Russia and China are challenging the ability of intelligence agencies to electronically travel there.  Generative adversarial networks (GANs) are enabling advanced deepfakes and impairing the ability to detect false information/personas and tailored social engineering.

Finally, blockchain technologies and cryptocurrency enable non-attributed payments and complicate the ability to “follow the money”.  And quantum computing can threaten communication security tools and enable the decryption of what was once secure data collected by adversaries.

Now think of these not as single problems you have the luxury of time to address, but as concurrent challenges simultaneously undermining traditional tradecraft methodologies.  The challenge is daunting.


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